Journal of biopharmaceutical statistics
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Sun et al. (2009) proposed an optimal two-stage randomized multinomial design that incorporates both response rate (RR) and early progression rate (EPR) in designing phase II oncology trials. However, determination of the design parameters in their approach requires evaluating huge numbers of combinations among possible values of design parameters, and thus requires highly intensive computation. In this paper we develop an efficient algorithm to identify the optimal two-stage randomized multinomial designs in phase II oncology clinical trials comparing a treatment arm to a control arm. ⋯ Some other techniques are also used to further improve its efficiency. Examples show that the proposed algorithm has more than a 90% reduction in computation time while having an acceptably low approximation error. This may enhance usage of the optimal two-stage multinomial design in clinical trials and also make it feasible to extend the design to more complicated scenarios.
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The Food and Drug Administration (FDA) draft guidance on adaptive design randomized clinical trials provides in-depth consideration of the difficulties that unblinded adaptation of clinical trial design might introduce. We provide extended discussion of these difficulties, with focus on the problems that the adaptive designs pose in the scientific interpretation of randomized clinical trial results, for regulatory authorities as well as for patients and caregivers who wish to make evidence-based decisions regarding the choice of treatment. ⋯ We examine the extent to which the adaptive designs do not meet the goals of having greater efficiency, being more likely to identify truly effective treatments, being more informative, and providing greater flexibility. We fully support the FDA's continued requirement of adequate and well-controlled confirmatory studies, complete with prospective, detailed specification of the entire randomized clinical trial design in a way that allows accurate and precise estimation of treatment effectiveness.
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The Food and Drug Administration of the United States issued a draft guidance on adaptive design clinical trials in February 2010. This draft guidance has attracted a lot of attention because of the increasing interest in adaptive trials by the pharmaceutical industry in recent years. ⋯ In addition, we share Pfizer's internal journey to promote efficient trial designs since 2005. Adaptive designs have been part of that journey.
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Patient-reported outcomes are important for assessing the effectiveness of treatments in many disease areas. For this reason, many new instruments that capture patient-reported outcomes have been developed over the past several decades. ⋯ As well as being of interest in its own right, the use of a minimum clinically important difference on the patient-reported outcome scale is likely to lead to sample size advantages. We illustrate the method with data on neuropathic pain when responder is defined by requiring at least some improvement in the Patient Global Impression of Change and when responder is defined by existing responder definitions.